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A Novel Mechanism for Flooding Based Route Discovery in Ad Hoc Networks Jian Li and Prasant Mohapatra GlobeCom’03 Speaker ︰ CHUN-WEI
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Outline Introduction PANDA Design PANDA-LO PANDA-LV PANDA-TP Simulation Conclusion
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Introduction Flooding based route discovery AODV,DSR…etc Broadcast storm problem In [11]”A Performance Comparison of Multi- hop Wireless Ad-hoc Networking Routing Protocol“ use Random Rebroadcast Delay (RRD) approach to solve the problem
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Introduction RRD approach is not the most suitable one in term of search for a better route RRD approach may choice the worst next - hop candidate S I J K L M D
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Introduction We propose to use location and velocity information in determining the rebroadcast delay time Positional Attribute based Next-hop Determination Approach (PANDA)
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PANDA Design Basic idea Discriminate neighboring node as good or bad candidate for the next hop Good candidate Shorter rebroadcast delay Bad candidate Longer rebroadcast delay Algorithm PANDA-LO (Location Only) PANDA-LV (Location & Velocity) PANDA-TP (Transmission Power)
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PANDA Design Assume Each mobile node is equipped GPS Location and velocity information
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PANDA Design – PANDA-LO The farther away node form the upstream node, the shorter rebroadcast delay
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PANDA Design – PANDA-LO Random value between 0 to t 1
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PANDA Design – PANDA-LO PANDA-LO may lead to fragile path Not consider the link lifetime
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PANDA Design – PANDA-LV Use both location and velocity information Estimating the link lifetime Choosing stable links as the next hop
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PANDA Design – PANDA-LV Θ
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PANDA Design – PANDA-TP In wireless sensor network, power conservation is more important than reduction of end-to-end delay Break a big single hop into several small hops Demonstrated the following example Small hops power consumption is smaller than a big single hop
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PANDA Design – PANDA-TP Assume ︰ P RXmin is the minimal receive power L is propagation loss
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PANDA Design – PANDA-TP (α is between 2 and 4)
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PANDA Design – PANDA-TP
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Simulation PANDA-LO and PANDA-LV Use the codebase of DSR in ns-2 simulator Simulation area is 1500×300 square meter 100 nodes uniformly deployed A node’s speed is uniformly distributed in the range of (0, 20) meter per second Transmission range is 250 meter
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Simulation
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PANDA-TP Simulation program by ourselves Simulation area is 1500×300 square meter Nodes can dynamically control their transmission range In the route discovery phase, the nodes used a fixed transmission range of 250 meter
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Simulation
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Conclusion PANDA approach can improving the performance, quality, and energy conservation of routing algorithm
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